UNIVERSITY OF VAASA 
 

FACULTY OF BUSINESS STUDIES 
 

DEPARTMENT OF MANAGEMENT 
 
 
 
 
 
 
 
 
 
 
  
 
 

Clement Kasongo 
 

ANALYSIS OF MECHANISMS THAT MOTIVATE KNOWLEDGE 
SHARING  

A Case Study 
 
 
 
 
 
 
 
 
 
 
 
 

Master’s Thesis in 
International Business 

 
 
 
 

 

 

VAASA 2015 





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TABLE OF CONTENTS                    page 

LIST OF FIGURES 7 

LIST OF TABLES 7 

ABSTRACT 9 

1. INTRODUCTION 11 
1.1. Background of the study 11 

1.2. Research Problems and Research Gap 12 

1.3. Research Question and Objectives 14 

1.4. Scope of the study 15 

1.5. Thesis Outline 16 

2. LITERATURE REVIEW 18 
2.1. Socio-Psychological Determinants of Knowledge Sharing 19 

2.1.1. Social Capital Theory 19 

2.1.2. Social Dilemma Theory 22 

2.1.3. Social Exchange Theory 30 

2.2. The Concept of Knowledge 32 

2.2.1 Typologies of Knowledge 34 

2.3. Knowledge as an Organizational Resource 37 

2.4. Knowledge Sharing 40 

2.5. The Role of HRM in Knowledge Sharing 42 

2.5.1. Recruitment and Selection 44 

2.5.2. Job Design 46 

2.5.3. Training and development 47 

2.5.4. Coaching and Mentoring 48 

2.5.5. Performance Appraisal and Compensation System 49 

2.5.6. Communities of Practice 51 

2.6. The Role of Organizational Culture in Knowledge Sharing 53



  



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2.7. Summary of the Literature Review 57 

3. RESEARCH METHODOLOGY 61 
3.1. Research Approach 62 

3.2. Methodological Choice 63 

3.3. Case study and selection procedure 63 

3.4. Time Horizon 66 

3.5. Data Collection 67 

3.5.1. Sample Characteristics 68 

3.6. Data Analysis 69 

3.7. Research Ethics 70 

4. EMPIRICAL FINDINGS 74 
4.1. Case Company 74 

4.2. Organizational factors motivating employee knowledge sharing 77 

4.2.1. Monthly meetings 79 

4.2.2. Management support 80 

4.2.3. Information Systems 81 

4.2.4. Informal meetings 83 

4.3. Organizational culture and its affect on knowledge sharing 84 

4.3.1. Equal and fair treatment at workplace 85 

4.3.2. Flat and flexible organizational hierarchy 86 

4.3.3. Team based work tasks 88 

4.4. HRM practices motivating knowledge sharing 89 

4.4.1. Recruiting, training, and retaining policy 89 

4.4.2. Compensation and reward system 90 

4.4.3. Job design 91 

4.5. Company Social structures, and their impact on employee knowledge sharing 92 

4.5.1. Employment relationship 93 

4.5.2. The role of trust 94 

4.5.3.  Personality traits 96



  



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4.5.4. National culture 97 

5. DISCUSSIONS AND CONCLUSION 98 
5.1. Discussion of the findings 98 

5.1.1. Organizational factors motivating employee knowledge sharing 99 

5.1.2. Organization culture and its effect on knowledge sharing 102 

5.1.3. HRM practices motivating knowledge sharing 105 

5.1.4. Company social structures, and their impact on employee knowledge sharing

 110 

5.1.5. Summary of the findings 114 

5.2. Theoretical contribution 116 

5.4. Managerial Implications 120 

5.5. Limitations and future studies 121 

REFERENCES 122 

APENDICES 137 
APPENDIX 1. Interview guide 137 

APENDIX 2: Consent form 141 

 

 

 

  



  



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LIST OF FIGURES 

Figure 1. Thesis Outline. 17 

Figure 2. Hierarchical Structure of Data, Information, and Knowledge. 33 

Figure 3. Generic Knowledge Types. 36 

Figure 4. How Communities of Practice Underpin Knowledge Processes. 52 

Figure 5. Cameron and Quinn's Organizational Culture Typology 55 

Figure 6. Mechanisms motivating employee knowledge sharing. 60 

Figure 7. Research Onion. 61 

Figure 8. Hierarchical organization. 76 

Figure 9. Modified Theoretical Framework 119 

 

LIST OF TABLES 

Table 1. The Potential Advantages and Disadvantages to Workers of Sharing their 

Knowledge. 23 

Table 2. Newell and Swan's three Types of Trust. 27 

Table 3. Characteristics of Tacit and Explicit Knowledge. 35 

Table 4. Overview of Collective Knowledge Types. 37 

Table 5. Attitudes and Behavior Relevant to Knowledge Management Initiatives. 43 

Table 6. HRM Practices Identified as Facilitating Knowledge Sharing. 44 

Table 7. Taxonomy of Knowledge-Intensive Firms. 66 

Table 8: Interview Schedule. 68 

Table 9: Domestic staff education level. 75 

Table 10. Summary of the findings 115 

 

  



  



	 9	

 
UNIVERSTY OF VAASA 
Faculty of Business Studies 
Author:  
Topic of the Thesis: 
                                      
Name of the Supervisor: 
Degree:   
                            
Master’s Programme: 
Year of Entering the University: 
Year of Completing the Thesis:  

 
 
Clement Kasongo 
Analysis of Mechanisms that Motivate 
Knowledge Sharing: A Case Study 
Professor Jorma Larimo 
Master of Science in Economics and 
Business Administration 
International Business 
2011 
2015                                       Pages: 143 

ABSTRACT 

In today’s fast-paced business environment, organizations have realized the significance 
of knowledge sharing as a strategic source of competitive advantage. This realization 
has led to increased attention from the academic community in the last two decades. 
However, despite the importance, existing research in this area have claimed 
insufficient attention to micro-level (individual) variables and relationships that lead to 
knowledge sharing.  

The purpose of this study was to analyze the mechanisms that motivate employee 
knowledge sharing. The empirical part of the study was conducted between May and 
June 2015, through a qualitative single case study of a Finnish company in a multi-
sector training, consultancy, and planning.  Data for the research were collected using 
both primary and secondary methods to ensure triangulation. Five semi-structured face-
to-face interviews were conducted and analyzed using inductive reasoning approach.  

The results suggest that human, cultural and social psychological factors are central to 
the success of knowledge sharing among employees. Further, HRM practices were 
found to help enhance human and social psychological factors that promote both 
individual capabilities, as well as, their willingness to share knowledge with others. 
Also, organizational cultural factors were found to play a crucial role in motivating 
employees to share knowledge with others. The study contributes to the theory by 
drawing attention to the significance of micro-level dynamics in knowledge sharing 
practices through the formulation of the theoretical framework. Furthermore, managers 
can use the results of this study to enhance the well-being of employees by actively 
implementing HRM practices that will promote and increase the organization’s 
knowledge base. 

KEYWORDS: Knowledge Sharing; Social Capital Theory; Social Dilemma theory; 
Social Exchange Theory; Human Resource Management Practices. 



  



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1. INTRODUCTION 

This chapter will briefly describe the background of the study and the strategy used to 

conduct the research. The chapter will also present the research problem, followed by 

research questions and objectives. Thereafter, the scope of the study will be given, and 

the structure and organization of the thesis will be presented. 

1.1. Background of the study 

Over the years, market shifts, technology advancement, competition growth among 

firms, and overnight product obsolete has brought challenges in integrating firm-wide 

resources. These resources have been recognized as the firm strategy for competitive 

advantage. According to Peng (2009: 4), “To stand out among the crowd, valuable, rare, 

and hard-to-imitate capabilities are a must”. Moreover, the resource-based view (RBV) 

affirms that organizational resources can result in organization competitive advantage 

(e.g. Barney 1991; Nonaka 1991; Liu & Phillips 2011). The RBV suggests that the firm 

must have resources that are superior to those of its competitors to have a competitive 

advantage. Furthermore, the RBV rests on two key assumptions: (1) resources vary 

across organizations, and (2) there must be no strategically uniquely valuable resources 

that are themselves either rare or imitable. Consequently, the control of these resources 

can lead to a firm’s competitive advantage, allowing it to outperform others. More 

importantly, competitors may not be in a position to challenge the focal organization 

due to the lack of similar resources (Barney 1991: 105-111).  

Additionally, there is an emerging importance in the strategic management of 

knowledge as a critical organizational resource that provides a sustainable competitive 

advantage (e.g. Nonaka & Tekeuchi 1995; Daveport & Prusak 1998; Foss, Husted & 

Michailova 2010; Mäkelä, Andersson, & Seppälä 2012). According to Hislop (2013: 2), 

prior studies show that there are three key assumptions to the importance of knowledge 

management in organizations’ management of their workforce. First, the assumption 

that the end of the twentieth century witnessed an enormous social and economic 

transformation, that resulted in knowledge becoming the key asset for organizations to 

manage (Spender & Sherer 2007: 6). A second key assumption is that the nature of 



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work has also changed significantly, with the importance of intellectual work increasing 

significantly (Sewell 2005: 685-6). The third, related, key assumption is that the 

effective management of its knowledge base by an organization is likely to provide a 

source of competitive advantage (e.g., Swart 2011; Barney 1991; Grant 1996;); 

productivity (Choi, Lee, & Yoo 2010); and performance and other capabilities (Haas & 

Hansen 2007; Liu & Phillips 2011). 

From the resource-based view of the firm’s standpoint, scholars have suggested that 

firms are dependent to some extent on the ability to create the knowledge required to 

adapt to their environments internally. The formal repositories and documentation are 

effective for capturing knowledge that can be easily communicated, but are unable to 

capture important 'tacit' knowledge (Polanyi 1966), which resides in key employees 

(Storey & Quintas 2001). This development is as a result of the highly complex 

knowledge that cannot easily be codified and is dependent on specific context, or a 

system of knowledge is difficult to transfer (Reychav & Weisberg 2009). Moreover, 

valuable and rare complex knowledge can be an important source of superior 

performance and sustainable competitive advantage (Spencer & Grant 1996: 8; Liu & 

Phillips 2011). Hence, the process of sharing complex knowledge within an 

organization becomes important (see Foss et al. 2010: 458.) 

1.2. Research Problems and Research Gap 

There has been an increased importance of knowledge management research, especially 

in the last two decades. Unfortunately, according to Foss et al. (2010), knowledge 

sharing is an area of inquiry that still requires much attention, and whose key variables, 

relationships, and implications are unclear. It is therefore not surprising that many 

organizations are left struggling with how to share their knowledge and that many 

knowledge management systems implemented in practice fail to achieve their original 

goals (Akhavan, Jafari & Fathian 2005). Therefore, for knowledge management 

initiatives to benefit organizations, the variables and relationships that lead to 

knowledge sharing must be better understood. The majority of previous research on 

managing knowledge has examined constructs and relationships at the macro level, 

generally at the firm level, leaving little work rooted in micro foundation at the 



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individual level (Foss et al. 2010). According to a study by Foss et al. (2010), 71 of the 

100 reviewed articles addresses macro-macro relationships. Only 20 studies analyses 

micro-micro interactions. 

Practically, this study seeks to fill this gap by including a focus on individuals; 

ultimately, only individual employees can contribute and draw from an organization’s 

knowledge base to share knowledge. Therefore, understanding an individual employee’s 

need and relationships may yield new organizational insights and lead to a better 

understanding of what mechanism influence individuals to share their knowledge in an 

organization. Moreover, if no specific assumptions are made about organizational 

members, it is difficult to theorize meaningfully their interaction, including how such 

interaction aggregates to organization-level knowledge sharing outcomes. The lack of 

attention to micro-foundations has the potential of making it difficult to come forward 

with managerial advice. Organizational design implementations that aim at influencing 

knowledge sharing but pay no attention to informal organization are likely to be 

misguided. This attributes to the limitations by the current literature to equip managers 

make decisions about how to incorporate knowledge sharing initiatives in existing 

organizational structures and cultures, and they lack robust research-based models for 

assessing the organizational costs and benefits of engaging in knowledge sharing. (ibid: 

467). 

Furthermore, how knowledge sharing on the level of organizational members adds up to 

organizational level knowledge sharing is an issue of concern. This issue has been 

treated in some detail in parts of the knowledge sharing literature and has been seen as a 

key issue since the early founding statements (notably Nonaka 1991). Likewise, it is a 

key theme in the organizational learning literature (Crossan Lane, White & Djurfeldt 

1999). Nevertheless, open issues remain. 

‘Knowledge aggregation’ is problematic because it is often not a matter of simply 

summing all the individual knowledge sharing activities (e.g. knowledge may be 

redundant), and because ‘knowledge aggregation’ is not independent of the 

organizational design. The first issue suggests that there is a limit to how much 

knowledge sharing should efficiently be undertaken in an organization. Efficient 



	 14	

organizational knowledge is seldom, if ever, identical to maximum organizational 

knowledge sharing. In fact, it has been argued that the key advantages of such 

mechanisms as pricing (Hayek 1945) and managerial authority (Demsetz 1988) is that 

they reduce the need for knowledge overlap, and therefore for knowledge sharing 

efforts. The broader lesson is that the aggregation of individual knowledge sharing to 

organizational knowledge sharing may be critically dependent on not just informal 

knowledge sharing networks (Tsai 2001), but also formal governance mechanisms. 

Such mechanisms not only influence the motivation to share knowledge, as argued 

earlier, but also influence the ability and the opportunity to do so. Organizational design 

variables such as specialization and departmentalization may be expected rather directly 

to influence knowledge sharing ability and opportunity. Therefore, this study will 

investigate this gap by looking at the extent to which such organizational variables 

moderate the relation between individual knowledge sharing behaviors and 

organizational knowledge sharing outcomes. 

Finally, the role of motivation has been recognized and emphasized in the knowledge 

sharing literature (e.g., Fey & Furu 2008; Liu & Phillips 2011). These studies have used 

different motivation theories such as social dilemma theory (Cabrera & Cabrera 2005), 

social capital and social exchange theories (Kankanhalli 2005). Therefore, the current 

study intends to investigate knowledge sharing using these theoretical frameworks (at a 

micro-level or the organization) given the insight they have provided in understanding 

employee knowledge sharing behaviors (e.g., Cabrera & Cabrera 2005; He, Qiao & 

Wei: 2009). 

1.3. Research Question and Objectives  

Following the research problems and gap discussed in the preceding section, the 

purpose of this study is to understand the mechanisms that motivate employees to share 

knowledge with others. To address this purpose, this study is divided into two parts. 

Firstly, the theoretical part of the thesis discusses previous research on knowledge 

sharing. Based on this, a theoretical framework will be derived. Secondly, the empirical 

case study will test the assumptions that arise from the theoretical framework. 

Moreover, using a qualitative case study, this thesis will focus on the organization’s 



	 15	

micro-level knowledge sharing. Specifically, answering the following research 

questions.  

RQ1: What mechanisms motivate employees to share knowledge with others? 

RQ2: How do these factors help facilitate knowledge sharing among employees? 

In order to answer the research questions, the following empirical objectives (EO) have 

been formulated, which will also provide triangulation on the topic. 

EO1: To find out how the organization motivate employees to share knowledge. 

EO2: To investigate how the organization’s culture affects employee knowledge sharing 

EO3: To identify HRM practices that motivates employee knowledge sharing 

EO4: To identify the different social structures embedded in the firm, and their impact 

on employee knowledge sharing 

This study utilizes the theories of social capital, social dilemma, and social exchange 

theory to understand individual-level motivating factors to knowledge sharing. The 

subsequent section will now discuss the delimitations and scope of the study. 

1.4. Scope of the study 

This study focuses on the individual level rather than organizational level knowledge 

sharing. The study aims at investigating the factors that motivate employees to share 

knowledge with work colleagues in the case company. Throughout this paper, the term 

‘knowledge sharing’ will be used interchangeably with terms, knowledge management 

initiatives, and knowledge transfer. This study defines Knowledge sharing as a personal 

responsibility for acquiring, processing and sharing of information. 

Furthermore, this study is limited to the internal investigation of the organizational 

climate, and how it affects knowledge sharing among employees at the chosen firm. 

Aside from this, the study will try to identify the different organizational social 



	 16	

structures, and their impact on employee knowledge sharing. For the theoretical 

approach, this study will build a bridge between the theoretical starting points, the 

results of the empirical research and the usability of the presented findings in practice. 

This approach will contribute to the enhancement of knowledge sharing among 

employees. This thesis also assumes that the findings will be able to contribute to the 

literature on knowledge sharing at a micro-level from the organization’s perspective. 

Central to this study is the work by Hislop (2013) on knowledge management in 

organizations. 

This study investigates HRM practices and how they facilitate knowledge sharing 

among employee. The study concentrates on identifying the activities within the 

organization aimed at managing the pool of human capital (employees) and making sure 

that the capital is employed towards the fulfillment of organizational goals (Wright, 

McMahan & McWilliams 1994: 301). This notion leads to recognizing two aspects of 

human resources, (1) the knowledge, skills and abilities of organizational members, and 

(2) employee behavior as the mediator in the relationship between a firm’s strategy and 

performance. (Wright et al. (1994: 304-305.)  

The study is conducted in a multi-expertise group of companies, with extensive 

international operations. However, due to the time limit, the sample population selected 

for this study is limited to four Training Managers within a company under the Group in 

Finland and one HR representative at the Group level. Thus, units falling outside this 

company fall outside the scope of this study. The following section gives an outline 

structure for the study. 

1.5. Thesis Outline 

This thesis is divided into five parts. The paper proceeds with a review of previous 

studies within the knowledge sharing literature. Thereafter, the qualitative case study 

method is discussed before presenting empirical findings and analysis regarding 

employees’ motivations for knowledge sharing. Finally, conclusions, including 

implications for managers, limitations of the research, and future research direction will 

be discussed. Figure 1 below shows an outline followed by this study. 



	 17	

 

 
 
 
1. INTRODUCTION 
  
 

 

 
 
 
2. LITERATURE REVIEW 

 
 
 
 
 
3. RESEARCH 
METHODOLOGY 

 
 
4. EMPIRICAL DATA  
 

 

5. DISCUSSIONS AND 
CONCLUSION 

 

Figure 1. Thesis Outline.  

v This chapter discusses and motivates the 
methodological issues connected to this study. 
The research approach, methodological choice, 
case study and selection procedure, data 
collection, data analysis, and ethical issues 
related to this study are discussed. 

 
v In this chapter the empirical data collected for 

the case study have been presented. The first 
section gives an introduction to the case 
company, and thereafter, findings from the 
interviews are presented. 

 

v In this chapter results from the interviews 
are discussed, following a within‐case 
analysis, and compared with the previous 
research discussed in chapter 2. 

 
v Conclusions are drawn, with  

Future research 
and recommendations  

given.   
 

v General background to the topic was  
 presented. The research gap was 

identified, leading to 
Research the question and objectives. 

 
v This chapter discusses the  

theoretical framework relevant to  
the study purpose and  

research question and  
objectives. 



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2. LITERATURE REVIEW 

This chapter casts light on the theoretical background for the study’s major constructs: 

knowledge sharing; the role of HRM in knowledge sharing; the role of organizational 

culture in knowledge sharing; and psychological determinant of knowledge sharing. 

Besides books, this study considered articles published in the last ten years against the 

key words ‘knowledge sharing’, ‘knowledge exchange’, and ‘knowledge transfer’. 

Furthermore, in spite of sustained efforts to be thorough in the search using 

Nelliportalli’s Business Source Premier, the possibility of having missed some articles 

has been acknowledged, but trust that the few potential unintentional omissions would 

not significantly modify the conclusions. 

To gain a systematic understanding of the mechanisms that motivate individuals to 

share knowledge with others, articles in top-tier management journals were reviewed. 

This approach is in consideration of the journal lists compiled by Foss et al. (2010) and 

Van Wijk et al. (2008). The review work also included Journal of Applied Psychology 

and Journal of Organizational Behavior, but no articles published in the considered 

period were found. Also, most important to the review work was the book by Hislop 

(2013) on knowledge management in organizations. 

This chapter will be organized as follows. Firstly, it is important to set the context of the 

literature review by discussing the theories on which this study is based. The concept of 

‘knowledge’, different types of knowledge, and how that knowledge has grown to be an 

organizational resource come next. Thereafter, comments of the previous treatment of 

the broad topic of knowledge sharing, and the role of HRM in such activities will be 

reviewed. Ideally, the work on knowledge sharing would analyze the individual level 

knowledge sharing. Thus, a review of previous studies on HRM practices that enhances 

knowledge sharing between individuals will be presented. Still, the multiple ways in 

which organizational culture may interact in influencing knowledge sharing outcomes 

will be discussed. Finally, an indication of the scope of the work presented in this 

chapter will be discussed. 



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2.1. Socio-Psychological Determinants of Knowledge Sharing 

In this section of the literature review, the theories that this study will utilize to give a 

better understanding of individuals’ motivating factors to share knowledge with others 

will be discussed. The socio-psychological theories of social capital theory, social 

dilemma theory, and social exchange theory, will be used to shed light on individual 

motivation to share knowledge.  

2.1.1. Social Capital Theory 

Social capital is defined as “the sum of the actual and potential resources embedded 

within, available through, and derived from the network of relationships possessed by 

an individual or social unit” (Nahapiet & Ghoshal 1998: 243). It represents embedded 

values, such as social ties, trusting relations, and value systems that facilitate actions of 

individuals (Tsai & Ghoshal 1998). In this regard, if one person does not behave 

accordingly, the relationship will not be successful. Moreover, in the process of creating 

social networks, social capital plays a role in enforcing behavioral norms among the 

various members of the network (Walker, Kogut & Shan 1997) as well as promotes the 

flow of information (Coleman 1988). Consequently, the formed network serves to 

develop social constraints, which directs the flow of information in the building and 

maintaining of social capital (Walker, Kogut & Shan 1997). Therefore, if the 

environment is rich in social capital, as identified by the existence of a strong network, 

trust, shared behavioral norms, reciprocity, and respect, the environment significantly 

contributes to the creation and sharing of knowledge (Nahapiet & Ghoshal 1998; 

Sharatt & Usoro 2003). This means that having strong social interactions and network 

ties positively influence knowledge acquisition (Yli-Renko, Autio & Sapienza 2001). 

According to Nahapiet & Ghoshal (1998), social capital consists of structural, cognitive, 

and relational dimensions. Prior knowledge management studies identified social ties, 

shared goals, and social trust as major constructs representing the structural, cognitive, 

and relational dimensions of social capital, respectively (e.g., Chow & Chan 2008; He et 

al. 2009; Nahapiet & Ghoshal 1998). Moreover, employees’ social ties, shared goals, 

and social trust have a combined effect on their knowledge sharing (He et al. 2009). 

They are independent variables representing the three dimensions and forming social 



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capital (Chow & Chan 2008), the change of which does not necessarily go with the 

same changes in the three dimensions. Therefore, this study considers these dimensions 

of social capital as the key drivers of forming employees’ knowledge sharing intentions: 

social ties (the structural dimension), social trust (the relational dimension), and shared 

goals (the cognitive dimension). 

The structural dimension refers to the way individuals relate one with the other. This 

dimension includes the social relations among network members as well as the overall 

network configuration, which considers factors such as structural holes, centralization 

and density of the network (Cabrera & Cabrera 2005: 722). In other words, this 

dimension involves the degree to which people in an organization relate, or are 

connected to each other (Bolino et al. 2005: 56). In essence, Nahapiet and Ghoshal 

(1998: 252) argue, “Who you know, affects what you know.” For example, social 

network theorists (e.g., Hansen 1999b) highlight some benefits concerning social 

relationships such as: (1) having access to valuable information and knowledge; (2) 

timing, that is “the ability of personal contacts to provide information sooner than it 

becomes available to people without such contacts” (Nahapiet & Ghoshal 1998: 252); 

and (3) referrals which provide “information on available opportunities to people or 

actors in the network” (ibid: 252-253), hence creating an environment for knowledge 

sharing  

The cognitive dimension of social capital is the extent to which employee within a 

social network shares a common perception or understanding, such as, a shared 

language. This enables communicating meaning, enabling access to information, as well 

as enhancing understanding among employees (Nahapiet & Ghoshal 1998: 252-253). 

Furthermore, this is also in line with Tsoukas & Vladimirou (2001: 985-991) who argue 

that, individuals’ ability to draw differences within a collectively generated domain of 

action is dependent upon the cultural tools they utilize with language being the most 

important one. Shared language (verbal or non verbal communication) is important not 

only that it provides an easy avenue for knowledge sharing, but also that integration of 

knowledge mainly through the creation of common cognitive schemata and 

frameworks, such as representations, analogies, and stories, which act as the means for 

integrating individual understandings and experiences. Subsequently, when there is a 



	 21	

shared vision among individuals or groups, it helps facilitate knowledge sharing and 

integration by providing meaning to their actions. Moreover, a shared vision represents 

the collective goals and objectives of the members of an organization and therefore 

employees who share a vision will be more likely share or exchange their resources’ 

(Tsai & Ghoshal 1998: 467). 

Finally, regarding the relational dimension, trust is a key mechanism by which social 

capital outcomes are achieved. It concerns relationships individuals or groups of 

individuals have developed with each other through a history of social interaction. 

According to Bolino et al. (2002: 510), the relational dimension of social capital is 

characterized by high level of trust, shared norms and perceived obligation, and a sense 

of mutual identification. Thus, people are more willing to experiment and take risks in 

sharing their knowledge. Accordingly, Mayer, Davis and Schoorman (1995: 712) 

defines trust as “the willingness to be vulnerable to the actions of another party”, where 

trustworthiness is “the quality of the trusted party that makes the trusting party willing 

to be vulnerable” (Levin & Cross 2004: 1479). The existence of high trust in a 

relationship produces certain outcomes such as cooperation, and sensitive information 

exchange (Mayer & Davis 1999). Moreover, trust is the ability for an individual to 

willingly and confidently act on the basis of someone’s words, actions, or decisions 

(McAllister 1995: 25). Therefore, the relational dimension of social capital can be said 

to be the strength of the relationship between people. However, relationships can vary 

from weak relationships to strong relationships characterized by high levels of trust. 

Furthermore, previous research has shown that knowledge sharing is common among 

relationships based on trust. This attributes to the fact that individuals are much more 

willing not only to share valuable knowledge but also learning from others (e.g., Mayer 

et al. 1995; Andrews & Delahaye 2000). Accordingly, as trust entails a willingness to 

take risks (Mayer & Davis 1999), it has also been argued that risk-taking individuals 

tend to engage in experimentation, accessing and integrating various pieces of 

information and knowledge. This behavior can result in the creation of new knowledge  

(Nahapiet & Ghoshal 1998: 245). 

Therefore, regarding knowledge sharing, structural and cognitive social capital 

determines whether or not individuals have the opportunity to share their knowledge 



	 22	

with others. Consequently, the opportunity to share increases when individuals spend 

more time interacting, not only because increased interaction leads to more frequent 

communication, but also because communication can be more effective due to the fact 

that these interactions also result in a shared common goal (Cabrera & Cabrera 2005: 

722). Moreover, the more time spent between people interacting, the better the 

understanding, and, as a result, creating an environment for learning. Hence increasing 

structural and cognitive social capital should help promote knowledge sharing (ibid). 

Similarly, social ties and having a shared goal should help to create an environment 

favorable for knowledge sharing and enhance knowledge sharing behaviors. 

Regarding the relational social capital dimension, individuals have the motivation to 

share what they know with others. Despite having an opportunity to share, an individual 

may not be willing to share if the environment is not favorable to do so. Therefore, to 

influence the willingness or motivation to share, employees need to be given an 

opportunity to trust and identify with one another. Also, relational social capital should 

help to encourage knowledge sharing and therefore, trust and group identification 

should encourage positive attitudes toward knowledge sharing and enhance knowledge-

sharing intentions and behaviors.  

Therefore, based on the knowledge of prior studies, this study suggest that social capital 

has an impact on individual knowledge sharing, as it involves the collaborative nature 

and environment of an organization. In other words, how much one is willing to share 

knowledge will depend on the atmosphere surround their workplace (e.g., job design, 

employee relationships, etc.). The preceding section looks at some of the factors that 

inhibit knowledge sharing among employees. 

2.1.2. Social Dilemma Theory 

According to Kollock (1998: 183), “Social dilemmas are situations in which individual 

rationality leads to collective irrationality.” Similarly, the decisions employees face 

about whether to participate in knowledge related activities have been likened to a 

classical public good dilemma (Cabrera & Cabrera 2002; Renzl 2008). A public good is 

a shared resource which members of a community or network can benefit from, 

regardless of whether they contribute to it or not, and whose value does not diminish 



	 23	

through such usage (Hislop 2013: 138). However, this may encourage people to ‘free-

Ride’ on other’s contribution.  Moreover, the dilemma for the employee is to choose 

between two choices: to share knowledge and contribute to the public good or hoard 

knowledge and act as a free rider. Therefore, in deciding how to act in such situations, 

employees are likely to attempt to evaluate individual benefits of sharing or hoarding 

knowledge. Table 1 below shows some of the advantages and disadvantages of 

employees’ sharing or not sharing their knowledge.  

Table 1. The Potential Advantages and Disadvantages to Workers of Sharing their 
Knowledge. 

Knowledge Sharing Advantages Intrinsic reward of process of sharing 
Group/organizational level benefits (such as 
improved group performance) 
Material reward (financial or non-financial) 
Enhanced individual status 

 Disadvantages Can be time-consuming 
Potentially giving away a source of power 
and expertise to others 

Knowledge Hoarding 
(Free-Riding) 

Advantages Avoids risk of giving away and losing a 
source of power/status 

 Disadvantages Extent of knowledge may not be understood 
or recognized 

 Source: Hislop (2013: 139) 

Further, Cabrera and Cabrera (2002) point out that the social environment may 

encourage or hamper successful knowledge sharing. Reward and development policies 

have to be adapted accordingly to overcome individuals’ reluctance to share knowledge. 

Such activities may include creating a trustworthy atmosphere or, even more 

comprehensively, a knowledge-friendly culture, establishing an atmosphere of openness, 

demonstrating commitment to training and development, showing leadership support, 

enlarging organizational commitment, showing the benefits of knowledge sharing, 

rewarding participation, and aligning work processes and tasks accordingly. Therefore, 

in understanding the socio-cultural factors, which shape employee’s willingness to 

participate in organizational knowledge sharing activities, it is important to take into 

account key factors, which can play a crucial role in shaping individual motivation to 

sharing knowledge. Hislop (2013: 140-150) highlights five key socio-cultural factors: 



	 24	

the nature of the employment relationship, the conflictual nature of intra-organizational 

relations, interpersonal trust, the role of personal identity, and the role of personality. 

Firstly, the nature of employment relationship means that about knowledge 

management initiatives, the interest of employees and their employers may not always 

be compatible (Hislop 2013: 151). Hislop (2013) argues that the origin of this tension is 

the inherent character of the employment relationship in private business organizations. 

Therefore, regarding employee’s knowledge, this tension relates not only to ‘who owns’ 

an employee’s knowledge but how and for what purposed such knowledge is used. For 

example, while management may feel that it is in the interest of the organization to 

encourage knowledge sharing, employees may be unwilling to do so if they perceive 

that such efforts will negatively affect them through diminishing their power and/or 

status. For instance, Liao (2008) found that, in terms of the direct effect, only reward 

and expert power had a direct impact on employees’ knowledge sharing. On the other 

hand, the importance of reference and expert power in building trust suggests that 

managers should develop both types of power, through managing employees so that 

they respect both the expert knowledge of employees and them as individuals.  

Furthermore, an indication that employees can perceive there to be differences between 

their interests and opinions and those of their managers relate to situations where they 

have been reluctant to express particular views (Hislop 2013:141). For instance, both 

Hayes and Walsham (2000) and Coborra and Patriota (1998) found that concerns held 

by a number of employees about the visibility of their opinions to senior management 

actively hindered them from participating in electronic exchange forums.  

Additionally, it is also important to realize that factors other than employment 

relationship affect an employee’s relationship with their employer, and can shape their 

knowledge-sharing attitude. Kim and Mauborgne (1998) suggest that ‘procedural 

justice’ is one such factor. Procedural justice represents the extent to which 

organizational decision-making processes are fair, with fairness being related to how 

much people are involved in decision-making, the clarity of communication regarding 

why decisions are made and clarity of expectations (Hislop 2013: 142). According to 

Kim and Mauborgne (1998), when all these factors are in place, employees will feel 



	 25	

valued for their intellectual capabilities and skills and that, experiencing such feelings 

can impact on employees’ attitudes towards knowledge sharing, “when they felt that 

their ideas and person were recognized through fair process, they were willing to share 

their knowledge and give their all” (Ibid: 332). Moreover, these finding also agrees with 

Han et al. (2010), whose study show that employee participating in decision making 

process provided them with a sense of psychological ownership over the decisions. 

Furthermore, this sense of psychological ownership was positively linked to employee 

levels of organizational commitment, which was in turn positively related to levels of 

knowledge sharing. 

 Secondly, the conflictual nature of intra-organizational relations relate to the issues 

of conflict, power, and politics in an organization (Hislop 2013: 142). Literature has 

shown numerous examples where such conflicts have affected attitudes to knowledge 

sharing (e.g., Currie & Kerrin 2004; Hislop 2003; Newell & Swan 2000). Hislop (2003) 

examined some case studies where organizational change was hindered by a lack of 

willingness among staff to share knowledge across functional boundaries. This 

unwillingness to participate in cross-functional knowledge sharing was suggested to be 

partly due to a history of inter-functional conflict and rivalry (see Currie, Waring & 

Finn 2008). Moreover, power and political environment are also associated with 

processes of knowledge sharing. For example, Willem and Scarbrough’s (2006) study 

of the relationship between social capital and knowledge sharing, found that what they 

referred to as ‘instrumental social capital’ was often used politically through a very 

selective form of knowledge sharing. 

According to Hislop (2013: 144), the typical neglect of conflict (and power and politics) 

in the mainstream knowledge management literature is largely due to the assumptions 

of consensus and goal congruence in business organizations that exist in the majority of 

the knowledge management literature. For example, Schultze and Stabell (2004) 

suggest that one dimension against which the knowledge literature can be characterized 

is the extent to which consensus in society and organizations prevails, with their 

analysis suggesting that consensus represents the mainstream perspective in the 

knowledge management literature. This is in line with Fox’s unitarist framework on 



	 26	

organizations, where everyone in an organization is assumed to have common interests 

and shared values (Fox 1985, as cited in Hislop 2013: 144). 

However, such a perspective on organizations can be challenged by evidence and 

analysis, which suggest the opposite, that conflict is an inherent and unavoidable feature 

of business organizations. For example, Schultze and Stabell (2004) suggest that 

potential conflict between management and employees is an inevitable part of the 

employment relationship. In contrast, Marshall and Brady (2001: 103), reflecting on the 

pluralist perspective (Fox 1985, as cited in Hislop 2013: 144) on organizations, where 

organizations are regarded as a coalition of different interest groups acting in a 

coordinated way, refer to the ‘frequent organizational reality of divergent interests, 

political struggles, and power relations’. This notion is also supported by the work of 

Buchanan (2008), where political behavior has been found to be a common feature of 

organizational life. 

However, the importance of taking into account of how conflict (and power and 

politics) shapes people’s willingness to participate in KM processes is not just due to 

the fact that conflict is an inherent/common feature of organizational life. But, it is also 

because the inter-relationship that exists between power and knowledge means, that 

knowledge can be used in a highly political way and is a resource people commonly 

draw on in dealing with situations of conflict. (Hislop 2013: 144) 

Thirdly, Interpersonal trust is an important aspect, with lack of trust likely to inhibit the 

extent to which people are willing to share knowledge with each other (e.g., Newell et 

al. 2007; Holste & Fields 2010). Trust can be defined as the belief people have about 

the expected behavior of others, and the assumption that one will honor his or her 

obligation. Moreover, a trusting relationship is based on an understanding of ‘give and 

take’ or reciprocity, in which everyone benefits (Hislop 2013: 145). However, 

knowledge sharing on the basis of trust arguably involves an unavoidable element of 

uncertainty, and can thus be a process, which produces and is shaped by emotion. For 

example, Holste and Fields (2010) investigated whether trust affected both the extent to 

which people share tacit knowledge with others, and the extent to which they use that 

tacit knowledge that has been provided by others. They found that trust in the 



	 27	

relationship with others played a key role in the sharing of tacit knowledge. However, 

that when it came to using tacit knowledge that had been provided by others, people’s 

trust in the competence of others was more primarily important. (ibid.) 

Research has found trust to be a complex concept (Hislop 2013: 146). One aspect of this 

is the distinction that can be made between a person’s general tendency to trust others 

and specific instances where trust exist in particular people (Mooradian et al. 2006). 

Moreover, some analyses introduce another layer of complexity by suggesting that trust 

has multiple dimensions and that it can exist in different forms. For example, Wang, 

Asleigh, and Meyer (2006) differentiate between calculus, knowledge, and 

identification-based trust. Similarly, Holster and Fields (2010) differentiate between 

affect- and competition-based trust. While Lee et al. (2010) talk of reliance and 

disclosure-based trust. Furthermore, Hislop (2013) suggest that each type of trust is 

developed in quite different ways and that they have a complex and mutually 

independent relationship. 

In Newell and Swan’s (2000) three-dimensional typology (see Table 2), companion-

based trust represents typically the strongest form of trust that can exist. This form of 

trust is developed over time and is built up gradually based on the perception of acts of 

goodwill and generosity. Thus, this form of trust cannot develop quickly, and requires 

extensive interaction to occur between people.  

Table 2. Newell and Swan's three Types of Trust. 

Types of Trust Description of Trust 
Companion Trust based on judgments of goodwill or friendship, built up over 

time 
Competence Trust based on perception of others’ competence to carry out relevant 

tasks 
Commitment Trust stemming from contractual obligations 

Source: Newell and Swan 2000 

Typically, interpersonal relations at work with colleagues will involve elements of all 

three forms of trust. Hence, if two colleagues who have known each other for some 

years have to collaborate in a particular project there may be an element of companion 

and competence-based trust due to the personal relationship that may exist between 



	 28	

them and their confidence in each other’s ability from knowing how they have 

performed on previous projects. Furthermore, there may be an element of commitment-

based trust due to promises that may have been made to particular tasks within 

particular timescales. However, the interpersonal trust may be based on one element 

alone. (Hislop 2013: 147.)  

Moreover, trust can be developed not only in individual people, but also within groups, 

teams, or organizations. Accordingly, these types of trust can have an equally important 

influence on an individual's willingness to share knowledge with others. For example, 

Renzl (2008) found that the greater the extent to which employees trust their managers, 

the more they are likely to share knowledge with colleagues. Ardichvili, Page, and 

Wentling (2003) reached a similar conclusion based on their analysis of what factors 

shaped workers’ willingness to contribute knowledge within a virtual community of 

practice. They talked about institution-based trust, which referred to the extent to which 

people trusted the organization to provide a working environment conducive to positive 

knowledge sharing and where people were unwilling to act opportunistically or 

excessively selfishly. They found that employees were likely to share knowledge to the 

virtual community of practice when this form of trust existed, as they were confident 

that others would not use this knowledge opportunistically. Finally, Usoro et al. (2007) 

suggest that the greater a person’s level of trust in, and identification with a particular 

workgroup or community, the more likely they will be willing to share knowledge with 

others in the community/group. 

Fourthly, Group identity deals with personal identity and how it affects the degree to 

and ways in which employees participate in organizational knowledge processes. 

Research has shown that the extent to which people feel a part of and identify with their 

organization, a project team a work group, a community of practice can significantly 

shape their willingness to participate in knowledge processes (Hislop 2013: 148). 

Furthermore, the literature on communities of practice (e.g., Usoro et al. 2007) shows 

that when people feel a sense of identity with a community, this facilitates the 

development of trust with other community members. Moreover, some studies have 

shown how employees’ identity with the particular functional group or business unit 

that they work in can influence their knowledge-sharing patterns. The studies argue that 



	 29	

people who have a strong sense of identity with their function or business unit show no 

willingness to share knowledge with people from outside of these areas (e.g., Hislop 

2003). For example, Rosendaal (2009) found that the more people identify with the 

teams they worked in, the more likely they were to share knowledge with other team 

members. Further, Currie and Kerrin’s (2003) study of the sales and marketing business 

of a UK-based pharmaceutical company found that the extent of strong subcultures 

within the sales and marketing divisions created unwillingness among staff to share 

knowledge across these functional boundaries. 

Fifthly, National cultural characteristics, a subject whose research is limited, as it has 

not been extensively researched, have been found to shape people’s attitude to 

knowledge processes (Hislop 2013: 151). Moreover, much of the analysis which links 

issues of national culture to knowledge management has come from studies of cross-

national collaborations, where cultural differences have been found to play a significant 

role (e.g., Inkpen & Piens 2006; Li 2010; Chen et al. 2010). The current study however, 

seeks to examine the influencing factors to share knowledge of employees of same 

national culture. 

According to Hislop (2013: 149), the assumption that a person’s culture background 

will shape their attitude to knowledge, and KM activities is something that is explicitly 

acknowledged within practice-based epistemology. Thus, this epistemology suggests 

that people’s knowledge and understanding, and also what counts as valid types of 

knowledge, will be shaped by cultural factors, including national cultural characteristics 

(e.g., Huang et al. 2008; McAdam et al. 2012). For example, Kanzler (2010) on 

Germany and Chinese scientists found that concerns about a loss of power were 

negatively related to the intention to share knowledge of the German, but not the 

Chinese scientists. Kanzler argued that this was because Germany society is more 

individualistic than Chinese society, and so, concerns about a loss of power due to 

sharing and ‘giving up’ knowledge were greater for the Germany scientists.  

Finally, research suggests that people with certain personality traits may have a more 

positive attitude to knowledge sharing than others (e.g., Cabrera & Cabrera 2005; 

Mooradian et al. 2006). All these studies make use of the five-factor personality model 



	 30	

(see sub-section 2.5.1), which suggest that human personality can be understood to be 

made up of five broad traits: openness, conscientiousness, extraversion, agreeableness, 

and neuroticism (Hislop 2013: 150). Openness (or openness to change) is the extent to 

which someone is imaginative, creative, and curious. Furthermore, extraversion can be 

defined as the extent to which someone is sociable, talkative, enthusiastic, and assertive. 

Similarly, neuroticism is the degree to which someone experiences negative emotions, 

such as anxiety, anger, or guilt. Likewise, conscientiousness can be defined, as the 

extent to which someone is careful, self-disciplined, hard working, dependable, and 

reliable. Agreeableness is when someone is generous, trustful, cooperative, and 

forgiving. As stated previously, this is a very under-explored topic and is inconclusive 

regarding exactly how personality relates to a person’s proclivity to share knowledge or 

their willingness to participate in any organizational knowledge processes (Hislop 2013: 

150).  

In summary, this section has revealed that understanding the theory of social dilemma is 

crucial to the success of knowledge sharing among employees. Moreover, a review of 

prior studies has shown mixed and diverse results on different constructs that influence 

employee knowledge sharing. However, the current study seeks to understand 

qualitatively how social dilemma in the case company affects employees' attitude to 

knowledge with others. The next subsequent section introduces the social exchange 

theory. 

2.1.3. Social Exchange Theory 

The social exchange theory (SET) derives from the fields of economics, psychology, 

and sociology. This theory suggests that individual actions are influenced by the desire 

to maximize profit and minimize costs. The economic exchange theory asserts that 

human relationships are as a result of rewards outweighing costs. For example if an 

investment reward gained is alleged to be less than its cost, the transaction ceases. 

However, exchange behavior is not influenced by economic desires alone, but also by 

psychological desires.  

A literature review has shown that SET is one of the models used in explaining 

knowledge sharing behavior (e.g. Blau 1964). Similarly, this theory is concerned with 



	 31	

people behavior, outcomes or benefits, environment and the interpersonal network 

between individuals (Blau 1964). According to Krok (2012), there are three cases to 

consider in which knowledge sharing can be beneficial. First, there is the reciprocity 

standard as mentioned earlier. People act, as they would want others to act towards 

them, or choose to share knowledge depending on reciprocity. Second, knowledge 

sharing is based on the intrinsic motivation, as stated in section 2.4 below. Lastly, 

knowledge sharing can yield recognition, which can either be monetary or none 

monetary recognition (such as, promotion, or positive thinking about someone). 

Accordingly, reciprocity indicates that people may demonstrate knowledge-sharing 

behavior with the intention of gaining positive rewards. Moreover, the SET also posits a 

similar thought line that individuals share their knowledge only when they perceive 

benefits after doing so. Therefore, the SET can be assumed as the foundation of mutual 

reciprocity, which argues, based on the benefit returns and states that one will not 

demonstrate certain behavior unless the expected results are positive (Blau1964). 

Contrary to trust, individuals will not consider certain activities when they feel 

uncertain about the related outcome. In other words, people will behave based on the 

trust they have for the system. Individuals develop their trust for another only when they 

are guaranteed that their transactions with the person will not cost them. Moreover, 

when there is an existence of trust between individuals they turn to cooperate easily 

with each other (Molm 2003). Consequently, this alludes to the fact that when 

individuals perceive other partners untrustworthy they will not exchange or cooperate 

with them since there is a certain level of uncertainty. Based on this discussion on trust 

one may conclude that trust within two individuals may encourage them to share their 

knowledge. The link between social exchange theory and trust is that knowledge being 

shared will not cause harm to the one offering it. 

In summary, this section has show that social exchange theory is crucial in determining 

the behavior of employees towards knowledge sharing. Previous studies have shown 

diverse results on the topic (see subsection 2.5.5. below). Moreover, results from prior 

studies have also shown that organizational rewards have commonly been studied 

within this topic and produced mixed results. The current study suggests that employees 



	 32	

will share information with each other provided the one receiving such information does 

not use it against the giver. In other words, the study investigates the issues related to 

social exchange centered on individual interactions, organizational context, and 

individual perception. The subsequent section introduces the concept of knowledge. 

2.2. The Concept of Knowledge 

The concept of “knowledge” has seen its growth since the 90s. Organizations have 

realized that better management of the learning process leads to efficiency. A review of 

the knowledge management (KM) literature reveals many different definitions and 

perspectives on knowledge. For example, Nonaka and Takeuchi (1995) adopt a 

traditional definition of knowledge as ‘justified true belief’. Belief is critical to this 

concept of knowledge because it is closely tied to an individual’s, or groups’, values 

and beliefs. From this perspective, knowledge derives in the minds and bodies of 

individuals. Paramount to the concept of knowledge is the process of learning. For it is 

through the process of getting to know and learning that knowledge is acquired. Chaffet 

and White (2011), suggest that when there is an integration of theory, information, and 

experience, it builds on to knowledge.  

Prior research on knowledge distinguishes between data, information, and knowledge. 

Miller and Morris (1999), for example, define knowledge as the intersection of 

information, experience, and theory. This definition is extended to include wisdom, 

described as successfully applied knowledge and which will often be tacit in nature. 

This concept of knowledge is shown in Fig. 2 below. Chaffey and White (2011: 208-

210) have defined data as discrete, objective facts, such as numbers, symbols, and 

figures. Data is usually without context or interpretation. Information however can be 

defined as data that adds value to the understanding of a subject and is usually in 

context. According to Chaffey and White (2011), information is the basis for 

knowledge, as it has no value until knowledge is applied to act upon it.  



	 33	

 

Figure 2. Hierarchical Structure of Data, Information, and Knowledge. 

Knowledge is similar to data and information, but it has a much deeper meaning among 

them. For instance, while information is a product of meaningful processing of data, 

knowledge is the value added to information (Davenport and Prusak 1998). According 

to Brown and Duguid (2000: 147-71), there are at least three important distinctions 

between information and knowledge. Knowledge entails a knower; it is much harder to 

detach, transfer, and share than information; and knowledge is much more difficult to 

assimilate and understand than information. Moreover, data, information, and 

Knowledge are interrelated in a hierarchical structure (see Figure 2) where the 

relationship between them is dynamic and interactive. The data and information can 

provide the building blocks of knowledge. Equally, knowledge can be used to generate 

data and information. Furthermore, knowledge shapes the type of information & data 

collected and the way it is analyzed.  

Wisdom 

Knowlege 

Information 

Data 



	 34	

While these and other such studies report a positive interaction between the above-

stated concepts, this study will adopt the definition of Davenport and Prusak (1998). 

This is because ‘knowledge’ as a concept has been explanation in a comprehensive 

manner: 

 “Knowledge is a fluid mix of framed experience, values, contextual information, and expert 
 insight that provides a framework for evaluating and incorporating new experiences and 
 information. It originates and is applied in the minds of knowers. In organizations, it often 
 becomes embedded not only in documents or repositories but also in organizational routines, 
 processes, practices, and norms.”(ibid: 5.) 

2.2.1 Typologies of Knowledge 

Hislop (2013: 21-22) examined two of the most common distinctions of knowledge 

typologies: tacit and explicit knowledge, and individual and collective or group 

knowledge. There is much agreement on the overall organizational implications of the 

distinction between tacit and explicit knowledge (e.g. Grant 1996; Nonaka 1991; 

Osterloh & Frey 2000; Spender 1996). These studies show that ‘there are two types of 

knowledge: explicit knowledge and tacit knowledge’ (Nonaka et al. 2000). Typically, 

this contrast is based on the work of Michael Polanyi (1958).   

Tacit-explicit contrast is widely used in analyses of organizational knowledge. 

According to Hislop (2013: 21), explicit knowledge is regarded as objective, standing 

above and separate from both individual and social value system.  Additionally, this 

type of knowledge is easy codified into a tangible form (ibid). Further, it is regarded as 

relatively less expensive because it is easy to transfer to others. Moreover, explicit 

knowledge is formal and systematic (Nonaka & Tekeuchi 1995). Explicit knowledge 

can be found in (hard) data records, and it is easily captured, manipulated and 

accessible.  

Tacit knowledge, as the basis for this thesis on the other hand, represents knowledge 

possessed by people, and which may importantly shape how they think and act, but 

which cannot be fully made explicit (Hislop 2013: 21; Nonaka & Tekeuchi 1995). It is 

mainly intangible knowledge that is typically intuitive and difficult to codify. Tacit 

knowledge is highly personal; it is hard to formalize and difficult to communicate to 

others (Ipe 2003; Sazali et al. 2010). According to Marzana, Jabar, Sidi and Selamat 



	 35	

(2010), the most pressing issue in an organization today is how to capture and codify 

employee’s tacit knowledge. In line with this, two of the most commonly referred to 

examples of tacit knowledge are the riding a bike or swimming. The knowledge 

possessed by people of how to carry out these activities is difficult to communicate, 

articulate, and share. Table 3 below shows the difference between tacit and explicit 

knowledge. 

Table 3. Characteristics of Tacit and Explicit Knowledge. 

Tacit Knowledge Explicit Knowledge 
Inexpressible in a codified form Codified 
Subjective Objective 
Personal Impersonal 
Context-specific Context independent 
Difficult to share Easy to share 

Source: Hislop (2013: 21) 

Furthermore, Osterloh and Frey (2000) also distinguished between tacit and explicit 

knowledge sharing. They argue that the different types of motivations (extrinsic and 

intrinsic) are important in sharing the two kinds of knowledge. Accordingly, Smith 

(2001) compared the distinctive roles of the two types of knowledge sharing. Their 

results show that a supportive and interactive learning environment is ideal for both tacit 

and explicit knowledge sharing. Moreover, Becerra, Lunnan and Huemer (2008) also 

found that the transfers of tacit and explicit knowledge, respectively, have different trust 

and risk issues. Furthermore, Reychav and Weisberg (2009) found that employees who 

are willing to share their tacit knowledge are likely to be willing to share their explicit 

knowledge to earn monetary and non-monetary benefits. Similarly, Huang, Davison, 

and Gu (2011) investigated the impact of trust and guanxi orientation about the 

intention to share knowledge in Chinese firms. They argue that tacit and explicit 

knowledge has different levels of impact, depending on the type of knowledge. 

While Nonaka’s theory is very prominent and widely referenced, some critics (Gourlay 

2006; Collins 2007) argue that there are still some limitations to it. Many aspects of it 

remain to be fully empirically evaluated. Furthermore, Hong (2012) relate to the 

conceptualization of tacit knowledge conversion and the extent to which it is a theory 



	 36	

that is relevant beyond the Japanese business and cultural context that it was developed 

in. However, Nonaka’s theory has been developed for more than twenty years and 

represents the single most significant theory in the area of knowledge management.  

Individual-group knowledge: Although knowledge can reside within individuals, 

there is a sense in which knowledge can reside in social groups in the form of shared 

work practices and routines, and shared assumptions or perspectives (Collings 2007; 

Hecker 2012). Spender (1996) merged the tacit-explicit dichotomy with the individual-

group dichotomy to produce a two-by-two matrix with four generic types of knowledge 

(see Figure 3) 

  

               Individual  

 

                  Social 

 

 

              
Explicit 

 

 

               CONSCIOUS 

 

 

                   OBJECTIFIED 

 

 

                  
Tacit 

 

 

               AUTOMATIC 

   

 

                  COLLECTIVE 

Figure 3. Generic Knowledge Types. 

 Source: Adapted from Spender (1996) 

According to Hislop (2013: 23), Objectified knowledge characterizes explicit group 

knowledge, for example, a documented system of rules, operating procedures or 

formalized organizational routines. On the other hand, Collective knowledge 

characterizes tacit group knowledge, knowledge possessed by a group that is not 

codified. This knowledge includes, for example, informal organizational routines and 

ways of working, stories and shared systems of understanding (Ibid). Accordingly, 

Hecker (2012) makes three distinctions of collective knowledge. Table 4 below 

summarizes this difference.  



	 37	

Table 4. Overview of Collective Knowledge Types. 

Types of 
Collective 
Knowledge 

Definition Locus Relationship to 
Individual 
Knowledge 

Origin 

Shared 
Knowledge 

Knowledge 
held by 
individuals in 
a group 

Individuals Intersection of 
sets of individual 
knowledge 

Shared 
experiences 

Complementary 
Knowledge 

Knowledge 
regarding the 
division of 
expertise 
within a 
group 

Relationships 
between 
knowledge sets 

Knowledge not 
included in any 
individual 
knowledge set but 
implicated by 
interdependencies 
between 
individual 
knowledge sets 

Specialized 
division of 
knowledge 
within group 

Artifact-
Embedded 
Knowledge 

Knowledge 
incorporated 
in collective 
artifacts 

Artifact Individual 
knowledge in 
explicated form 

Codification 
and 
explication of 
knowledge 

Source: Hecker (2012: 430) 

In summary, a review of the literature shows that the categorization of knowledge is 

significant to the understanding of employees’ knowledge sharing behaviors. Moreover, 

the difference between explicit- and tacit knowledge sharing, make it likely that they 

related to various levels of organizational rewards, satisfaction, and social capital. In 

this thesis, knowledge sharing intention refers to the belief that one will engage in a 

tacit knowledge-sharing act. While explicit knowledge sharing intention is belief that 

one will engage in explicit knowledge sharing act (Bock, Zmud, Kim & Lee 2005).  

2.3. Knowledge as an Organizational Resource  

According to the knowledge-based theory of the firm, knowledge that is difficult to 

replicate is firm-specific knowledge. It builds from and links to existing knowledge 

within an organization and is related to firm-specific products, services or processes 

(Wang, He & Mahoney 2009). The Knowledge-based theory of the firm also assumes 

that organizations provide a more efficient mechanism than markets do for the sharing 

and integration of knowledge between people. 



	 38	

The central idea stemming from the knowledge management literature that it is 

important for organizations to manage their workforce’s knowledge, flows from some 

key findings. For example, that “some think the ‘knowledge turn’ a matter of macro-

historical change; citing Drucker, Bell, Arrow, Reich or Winter. They argue that, “we 

have moved into an Information Age wherein knowledge has become the organizations’ 

principal asset” (Spender & Scherer 2007: 6). Furthermore, Sewell (2005: 685-6) 

assumes that the aspect of work has changed from the physical toil of manufacturing to 

the world of working more with minds than our hands. Moreover, “a firm’s competitive 

advantage depends more than anything on its knowledge: on what it knows – how it 

uses what it knows – and how fast it can know something new.” (HR Magazine 2009: 

1). Therefore, this thesis assumes that it is not just the realization of the organization’s 

specific resources, but the management of those resources that makes an organization 

outperforms others.  

Accordingly, these studies illustrate the fact that, first, the end of the twentieth century 

witnessed an enormous social and economic change, which resulted in knowledge 

becoming a significant asset for organizations to manage. Secondly, that the nature of 

work has also significantly changed, with the importance of intellectual work notably 

increasing. Thirdly, that an organization’s active management of its knowledge base is 

likely to provide a source of competitive advantage. For example, Bogner and Bansal 

(2007) conducted research, which tested certain aspects of the KBV. Specifically, they 

examined whether an organization’s ability to create and utilize new knowledge links to 

business performance. In their study, they used patent-intensive industries 

(Pharmaceuticals, semiconductors, forest products, oil and gas, and automotive). Two of 

the hypotheses that their research data supported, which they argued provided support 

for the KBV of the firm, were that first; business performance strongly relates to an 

organization’s level of knowledge creation.  Secondly, that business performance also 

relates to an organization’s ability to ‘recycle’ new knowledge and use it to improve 

future organizational knowledge creation activities. Thus, this thesis will add to the 

research finding that there is an association between individual motivations and 

organization wide knowledge sharing from a multi-sector training, consultancy, and 

planning perspective. Thus, it is likely to provide a source of competitive advantage 

(e.g. Foss, Minbaeva, Pedersen & Reinholt 2009).  



	 39	

Research on knowledge sharing often is associated with enhanced organizational 

capabilities. According to Prahalad and Hamel (1990: 84-91), it is often the attribute of 

individuals that characterizes the core competency of an organization. This attribute is 

because the knowledge and capabilities of individual employees within an organization 

are significant in ensuring organizational competitiveness (Pfeffer 1994:18-19). 

Accordingly, organizational knowledge and the sharing of it has become a topic of 

interest (e.g., McEvily & Chakranarthy 2002; Nonaka & Takeuchi 1995; Tsang 2002). 

Prior studies suggest that the concept of knowledge is far broader and richer than the 

concept of data or information, as seen in section 2.2. While individual knowledge is a 

fundamental organizational resource, it is the collaborative knowledge that determines 

its sustainable competitiveness (Hoops & Postrel 1999: 838). 

Prahalad and Hamel (1990:18-19) define core organizational competencies as the 

collective organization learning concerning knowledge that is hard to imitate by 

competitors (e.g., production, marketing, and technological knowledge). Likewise, Leif 

Edvinsson and associates (2004, as cited in Chowdhury 2005: 312) suggest that the 

developing of an organization-wide knowledge base and effective utilization and 

creation of new knowledge is significant in ensuring innovation and performance. 

Therefore, a well-implemented knowledge sharing processes can enhance an 

organization’s knowledge base and competitiveness (Andrews & Delahaye 2000; 

McEvily & Chakranarthy 2002, cited in Chowdhury 2005: 312). Moreover, sharing of 

tacit knowledge is a challenging but crucial task of developing organizational 

knowledge (Chowdhury 2005: 312). Both tacit and related natures of complex 

knowledge make it difficult to share. Similarly, complex knowledge sharing is 

considered to be a spiral process, which starts at the individual level and expands to 

greater organizational communities (ibid). According to Nonaka (2007: 165), 

socialization and combination are two crucial processes in an organization’s effort to 

develop and leverage its knowledge base that starts with individual knowledge. 

Specifically, socialization involves the exchange of knowledge between individuals by 

observation, imitation, and practice through informal interactions during work related 

tasks. On the other hand, combination involves the integration of disconnected shared 

knowledge into complex sets of a knowledge base for the organization (ibid). 

Furthermore, since both processes require active collaboration between individuals, 



	 40	

sharing of complex knowledge can only be achieved through social structures that 

comprise of trust and cooperation (Rastogi 2000: 47). Thus, mutual trust fosters 

interpersonal complex knowledge sharing. 

In summary, this section has shown that knowledge, as an organizational resource needs 

to be managed well to maintain the organization’s competitiveness. It has demonstrated 

that there is a consensus among researchers on the importance of the individual 

knowledge to the organizational-wide performance. Additionally, it has also been seen 

that it is the collaborative knowledge that determines sustainable competitiveness, 

despite its complexity. However, sharing of knowledge will not just take place without 

the willingness of individual, and very few studies have been carried out regarding 

intentions to share knowledge. Thus, this thesis seeks to fill this gap by finding out what 

motivates employees to share their knowledge with others. 

2.4. Knowledge Sharing 

Knowledge sharing in this study is defined as the process of mutually exchanging 

knowledge and jointly creating new knowledge (Wang & Noe 2010: 117). This 

definition is significant in that the extent to which knowledge sharing occurs between 

employees determine team and organizational level knowledge (e.g., Cabrera & Cabrera 

2005; Polanyi 1966). Moreover, knowledge sharing is an important part of developing a 

knowledge-based competitive advantage (Alwis & Hartmann 2008; Grant 1996). 

According to Polanyi (1969), knowledge sharing is a deliberate subjective act, which 

makes knowledge reusable by other people through knowledge transfer. It suggests 

collaboration of individuals who work towards a common goal (Boland & Tenkasi 

1995). Wang and Noe (2010) provide a comprehensive literature review on knowledge 

sharing in organizations. They identified five areas of emphasis of knowledge sharing 

research: organizational context, interpersonal and team characteristics, cultural 

characteristics, individual characteristics, and motivational factors.  

Similarly, Fey and Furu (2008), look at which organizational policies lead to knowledge 

sharing between multinational units. Based on 164 MNC subsidiaries in China and 

Finland, their study show that, the transfer of tacit knowledge, which is also critical to 



	 41	

MNCs, is especially problematic and often dependent on informal interactions among 

individuals and organizations. The current study focuses on knowledge sharing as 

rooted in individual behaviors and their motivation to share knowledge with others. 

Organizations have recognized the need to share knowledge. Knowledge sharing often 

involves mutual exchange among individuals, including sending and receiving 

knowledge. Moreover, it is a social act based on a sender-receiver relationship that 

involves communicating one’s knowledge to others as well as receiving others’ 

knowledge. In other words, individuals serve as knowledge creators and knowledge 

receivers. They create knowledge by exchanging their ideas and experience through 

social relations. As a receiver of knowledge, individuals seek and interpret the 

knowledge before transferring it to any repository (Nonaka & Tekeuchi 1995). This 

view means that creation and sharing of knowledge depend on the willingness of an 

individual who has to take initiative for knowledge to be shared or horde. 

For instance, an employee is made known of a work problem faced by a colleague. The 

employee has the solution to the problem. The employee may share or may not share 

the knowledge with the co-worker. Therefore, it is up to him or her to share the 

knowledge. The decision to share the knowledge may be influenced by his or her 

personal beliefs on knowledge sharing. The example indicates that individuals serve a 

central role in the process of knowledge sharing. According to Nonaka and Tekeuchi 

(1995), knowledge sharing will not be successful within an organization without the 

involvement of humans. Therefore, this thesis will show that it is important to 

understand individual factors that influence knowledge sharing among employees. 

While researchers have given considerable attention to organizational level 

mechanisms, they seldom have, if ever, explicitly considered individual mechanisms 

that foster knowledge sharing motivation (Foss et al. 2010). The following section will 

review the role of HRM, and how different HRM practices have contributed to 

individual motivation to knowledge sharing.  



	 42	

2.5. The Role of HRM in Knowledge Sharing 

Prior studies have shown that Social and cultural factors are significant in creating a 

successful knowledge sharing culture. This finding is primarily so because such factors 

have increasingly been recognized as fundamental in determining the workers’ 

willingness to participate actively in knowledge management activities. Inevitably, this 

has led to organizations putting up deliberate measures of managerial practices to 

encourage employees’ participation in knowledge management activities and initiatives. 

This section focuses on how different HRM practices can impact on individual 

employee’s attitude toward and participation in knowledge sharing.  

Accordingly, the attitudes and behaviors that are relevant to knowledge management 

initiatives are outlined in Table 5 below. Thus, it can be seen that HRM practices not 

only help create a positive attitude towards, and a willingness to participate in 

organizational knowledge sharing activities but also enhance employee commitment 

and loyalty to their employer. This notion is because, if employees are not committed 

and loyal to their organizations, there is a risk that organizations will lose any tacit 

knowledge those employees possess through staff turnover. Therefore, HRM practices 

concerned with supporting organizational knowledge sharing efforts should be 

concerned as much with developing the commitment and loyalty of workers as they are 

with persuading them to share, collect, or create knowledge. Hislop (2013: 220.) 

Hislop (2013: 221-23) considers three separate reasons why HRM practices can help 

produce the type of behavior and attitudes that are necessary to make knowledge 

sharing efforts successful. First, making links between the share/hoard dilemma as 

outlined in section 2.1, and the concept of motivation, HRM practices can be used to 

motivate employees positively to participate in knowledge sharing. Secondly, HRM 

practices can be utilized to support and facilitate organizational knowledge management 

activities through developing employees’ organizational commitment.  Moreover, it has 

been suggested that commitment may be an important variable, which mediates the 

relationship between HRM practices and knowledge sharing. Lastly, it is suggested that 

HRM practices can facilitate knowledge sharing through positively influencing the type 

of social-cultural factors, which have been shown to be crucial to employee 



	 43	

participation in knowledge sharing. Therefore, this study attempts to investigate 

empirically how HRM practices help foster knowledge sharing among employees and 

the types of practices embedded at the firm in support of knowledge sharing initiatives. 

Table 5. Attitudes and Behavior Relevant to Knowledge Management Initiatives. 

Attitudes Behaviors 
Positive attitudes towards knowledge 
management initiatives 

Active participation in knowledge 
management initiatives 

Level of loyalty and commitment to the 
organization, and the goals it is perusing 

Having continuous employment for 
significant periods 

Source: Hislop (2013: 221) 

In considering motivation, it is necessary to differentiate between intrinsic and extrinsic 

motivation. Intrinsic motivation refers to the pleasures and positive feelings people can 

derive from simply carrying out a task or activity, rather than for any reward derived 

from doing so.  In contrast, extrinsic motivation refers to the external rewards people 

derive from carrying out a task, such as money. Therefore, in terms of linking HRM 

practices, motivation, and knowledge sharing, HRM practices can be utilized to provide 

both intrinsic and extrinsic motivations for undertaking knowledge sharing activities. 

For example, concerning intrinsic motivation, HRM practices can be used to design jobs 

that are intrinsically interesting and challenging, and which thus encourage and 

motivate employees to utilize and share their knowledge. On the other hand, HRM 

practices such as reward systems can be used to motivate extrinsically employees to 

participate in knowledge sharing through offering financial incentives.  

Gagne (2009), present a model of knowledge-sharing motivation based on a 

combination of the theory of planned behavior (TPB) and self-determination theory 

(SDT). She proposes five important predictors of attitudes, need satisfaction, and 

sharing norms: staffing, job design, managerial styles, performance appraisal and 

compensation systems, and training. Hislop (2013) added coaching and mentoring, and 

communities of practice (CoPs) to the list. These can be developed and managed in 

ways that will influence knowledge-sharing behavior in organizations. Table 6 

summarizes HRM practices identified as supporting knowledge sharing, which this 

study proposes as facilitating employee motivation to share knowledge with others. 



	 44	

Table 6. HRM Practices Identified as Facilitating Knowledge Sharing. 

HRM 
practices 

How it facilitates Knowledge 
Sharing 

Authors 

Recruitment 
and selection 

Recruit people whose values 
‘Fit’ the organizational culture, 
and have personalities 
conducive to KS 

Swart & Kinnie 2003; Robertson & 
Swan 2003; Cabrera & Cabrera 
2005; Matzler et al. 2011; 
Mooradian et al. 2006 

Job Design Introduce challenging work 
tasks, adopt collaboration way 
of working  

Foss et al. 2009; Robertson et al. 
2003; Chen et al. 2011b; Horowitz 
2003; Khatri et al. 2010; Kuo & Lee 
2011; Holste & Fields 2010; Kase et 
al. 2009 

Training and 

Development 

Introduce formal & social 
programs, adopt training 
programs that best fit the 
organization’s KM process 

Kase et al. 2009; Robertson & 
O’Malley 2000; Hunter et al. 2002; 
Garvey & Williamson 2002; Nohria 
& Tierney 1999 

Coaching & 
mentoring 

Introduce social exchange 
programs, introduce programs 
that support interpersonal 
relations, intra-team working 

Garvey & Williamson 2002; 
Harrison & Kessels 2004; 
Karkoulian et al. 2008; Kets de 
Vries 1991; Orlikowski 2002; Lee et 
al. 2011; Swart & Kinnie 2003 

Performance 
Appraisal & 
Compensation 

Adopt a reward system that fits 
an organization’s KM strategy, 
introduce non-financial 
rewards, adopt a group focused 
reward system 

Cabrera & Cabrera 2005; Oltra 
2005; Hansel et al. 1999; Osterloh & 
Fey 2000; Fahey et al. 2007; Milne 
2007; Nayir & Uzuncarsilli 2008; 
O’Dell & Hubert 2011; Teo et al. 
2011; Paroutis & Al Saleh 2009 

Communities 
of practice 

CoPs support by management, 
simplify the communication of 
Knowledge; adopt individual 
and group learning 

Hughes et al. 2008; g Moran 2010; 
McLeod et al. 2011; Bertels et al. 
2011; Bradley et al. 2011; Bettiol & 
Sedita 2011; Hislop 2013 

Source: Adapted from Gagne 2000; Hislop 2013 

2.5.1. Recruitment and Selection 

Knowledge management literature according to Hislop (2013) shows that there are two 

ways in which recruitment and selection processes can help support knowledge 

management activities. First, recruiting people whose values are compatible with the 

existing organizational culture, and secondly, individuals with personalities that are 

conducive to knowledge sharing (e.g., Swart & Kinnie 2003; Robertson & Swan 2003). 

According to Hislop (2013: 224), recruiting people whose values and norms are 

compatible with those of an organization, help facilitate a sense of identity among new 



	 45	

recruits with their employer and work colleagues. Additionally, it helps provide a 

suitable foundation for the development of strong trust-based relations between new 

recruits and their colleagues. For example, Chen, Hsu and Lin (2011a) investigated how 

a range of different HRM practices affected the willingness of people within R&D 

teams in Taiwan to share knowledge. All the R&D teams surveyed were in high-

technology industries. They analyzed the surveys of over 200 employees from fifty 

separate R&D teams. Overall, they found that most of the HRM practices examined did 

affect people’s knowledge sharing behaviors. The current study seeks to investigate 

HRM practices using semi-structured interviews in a single case study. 

Furthermore, how personality relates to knowledge-sharing attitudes is a topic that is 

significantly under-researched, with very few empirical studies being done into this 

topic (Hislop 2013: 224). Moreover, while prior research use the five-factor personality 

model (openness, extraversion, neuroticism, consciousness, and agreeableness), they 

reach different conclusions about which personality traits positively influence 

knowledge-sharing attitudes (e.g., Cabrera & Cabrera 2005; Matzler, Renzl, Mooradian, 

von Krogh & Mueller 2011; Mooradian, Renzl & Matzler 2006). Accordingly, Cabrera 

and Cabrera’s (2005) research, based on a survey of a single Spanish organization, 

found that the ‘openness to change’ personality variable relates to a positive knowledge-

sharing attitude. On the other hand, Mooradian et al.’s (2006) study, also based on a 

survey of a single organization, found a link between ‘agreeableness’ and positive 

knowledge-sharing attitudes. Finally, Matzler et al.’s (2011) study, based on a survey 

conducted within a single Australian company, found that both agreeableness and 

conscientiousness positively relate to knowledge-sharing attitudes. The results from 

these studies cannot be generalized because they are all based on single organization 

studies. This current study, however, tries to extend this generalizability through a 

single case study using the same research question but tested on a different population. 

In summary, this section has shown that how organizations recruit its employees play a 

major role in employee knowledge sharing motivation. Literature has shown that 

organizations need to find 'fit' between individual values and that of the organizational 

culture to enhance knowledge sharing among the workforce.  However, the literature 

review has also shown that there is a lack of consensus of prior studies on which 



	 46	

specific personality traits promote knowledge sharing among workers. This study, 

therefore, seeks to identify what factors motivate employee knowledge sharing. The 

subsequent section discusses the relationship between job design and employee 

knowledge sharing.  

2.5.2. Job Design 

Jobs contain characteristics that influence different kinds of motivation towards 

knowledge sharing, which have different effects on individual knowledge sharing 

behavior (Foss et al. 2009: 872). According to Hislop (2013: 224), work should have 

three key features. First, it should be exciting and thought provoking. Secondly, 

employees should have high levels of autonomy concerning decision-making and 

problem solving. Lastly, it should encourage and require interpersonal collaboration. 

This categorization compares with Foss et al. (2009: 872) who asserts that job 

characteristics, such as task identity, autonomy and feedback, determine different 

motivations to share knowledge. This motivation in turn predicts employees’ knowledge 

sharing behaviors (ibid). For example, Chen, Zhang and Vogel (2011b) conducted a 

study into the link between conflict and knowledge sharing in some Chinese software 

companies. Their results suggested that interpersonal knowledge sharing would be 

encouraged if employees had both thought-provoking and meaningful work tasks and 

had high levels of autonomy.  

Additionally, in line with the first characteristic, work should also provide opportunities 

for employees to develop continuously their knowledge and skills (e.g., Robertson & 

O’Malley Hammersley 2000; Swart & Kinnie 2003). Moreover, the significance of 

having interesting and challenging work is also supported by the findings of Horowitz, 

Heng and Quazi’s (2003) study of Singaporean knowledge workers. This study found 

that managers for helping to retain their knowledge workers ranked providing 

challenging work as the most important factor. Similarly, Han, Chiang and Chang 

(2010), as seen earlier, found that participation in decision-making positively linked to 

levels of organizational commitment and knowledge sharing. 

Furthermore, in terms of autonomy, prior studies suggest that knowledge workers also 

place much importance on having high levels of autonomy at work (Khatri, Baveja, 



	 47	

Agarwal & Brown 2010). For instance, a study by Robertson and Swan (2003) found 

autonomy to be important to the consultants, and extended to the projects they worked 

on. It also showed in the selection of the training and development activities they 

undertook, work clothing, and work patterns (ibid). Finally, Kuo and Lee’s (2011) study 

into empowering leadership concluded that providing workers with high levels of 

autonomy was likely to help with the development of knowledge-sharing culture. 

The third feature of work tasks argued to encourage worker’s participation in 

knowledge management activities is that they should require and/or encourage 

collaboration amongst people. This is because collaborative working makes knowledge 

sharing a central feature of work activities (Holste & Fields 2010; Kase, Paauwe, & 

Zupan 2009).  Moreover, it is likely to facilitate the development of the type of strong 

interpersonal relations, which are conducive to interpersonal knowledge sharing (ibid). 

In summary, job design may, therefore, be an important avenue for firms that want to 

benefit from employees’ sharing of relevant knowledge. This consideration may be 

particularly relevant when the risk of highly knowledgeable employees leaving the 

organization or when the high costs of retaining such talent materialize, as seen above 

(Foss et al. 2009). Moreover, these are pressing problems for many consulting, 

accounting, and professional services firms that knowledge sharing may alleviate (ibid).  

2.5.3. Training and development 

As outlined in the previous section, providing opportunities for self-development can be 

integrated into the way people’s work activities are organized. However, it can also be 

achieved by providing appropriate opportunities to undertake formal training (Hislop 

2013: 225). Previous studies on the topic suggest that knowledge workers regard the 

provision of such opportunities by their employers as vital (e.g., Hunter, Beaumont & 

Lee 2002; Robertson & O’Malley, Hammersley 2000). Consequently, the provision of 

such opportunities is critical for employers, as without supporting continuous 

development, staff may be likely to leave. According to Garvey and Williamson (2002), 

the most useful sort of training to promote a culture of learning and knowledge 

development is not investing in ‘narrow’ skills-based training. However, they suggest 

training with a broader purpose to encourage reflexivity, learning through 



	 48	

experimentation, and how to conduct critical dialogues with others. Furthermore, 

Hansen, Nohria and Tierney (1999a) also suggest that the type of training provided 

should reflect the particular approach to knowledge management an organization 

adopts. For example, about their distinction between codification- and personalization-

based approaches to knowledge management, they argue that the provision of IT-based 

training be relevant for organizations pursuing a codification-based strategy. Whereas 

training to develop interpersonal skills and team working is most appropriate for 

organizations pursuing a personalization-based knowledge management strategy (ibid). 

Additionally, some studies into the role of Web 2.0 technologies to facilitate knowledge 

management suggest that the provision of training on the use of such technologies is 

likely to encourage employees to use them for knowledge sharing (e.g., Paroutis & Al 

Saleh 2009; Teo, Nishant, Goh & Agarwal 2011). Finally, Kase et al. (2009) suggest 

that one of the knowledge-related benefits of training is that it facilitates the 

development of good interpersonal relations between those undertaking it. This 

relationship is likely to encourage such people to share knowledge with each other in 

the future. 

2.5.4. Coaching and Mentoring 

Coaching and mentoring in organizations can facilitate the informal sharing of 

knowledge (e.g., Garvey & Williamson 2002; Karkoulian, Halawi & McCarthy 2008; 

Kets de Vries 1991). Accordingly, coaching and mentoring are both concerned with the 

sharing of knowledge between a relatively experienced person, the mentor or coach, and 

someone less experienced, the mentee (Wilson & Ellman 1990). However, they differ 

from each other on some issues. First, while mentoring has an indefinite timescale, 

coaching is for a set duration. Secondly, coaching is more structured concerning 

organization, for example, occurring at set regular times, for specific time periods. 

Finally, while coaching concerns the development of relatively narrow and specific 

skills and knowledge, mentoring is less focused in this way. (Hislop 2013: 226.) 

However, both coaching and mentoring can take many forms. For example, mentoring 

can be done in high-formalized ways, or relatively informally, and coaching can be 

done on a one-to-one basis or in groups. Some brief examples provide the knowledge-



	 49	

sharing benefits of mentoring and coaching. First, in the software company examined 

by Swart and Kinnie (2003), mentoring was used to facilitate cross-project knowledge 

sharing. Secondly, Kets de Vries (1991) in evaluating a single, intensive group coaching 

activity found that the development of trust among participants in this activity 

facilitated interpersonal knowledge sharing. Thirdly, Karkoulian et al. (2008), in a study 

of mentoring in Lebanese banks, found that informal mentoring had a positive impact 

on knowledge sharing behaviors. Finally, in the study of leadership by Lee, Gillespie, 

Mann and Wearing (2010), one of the ways intra-team trust and knowledge sharing was 

through a process of mentoring. This process involved pairing experienced team 

members with less experienced ones. Thus setting up and facilitating both coaching and 

mentoring activities represents another way for organizational management to facilitate 

interpersonal knowledge sharing. 

2.5.5. Performance Appraisal and Compensation System 

A literature review in the area of reward has shown no consensus regarding how 

systems can best be used to support knowledge management activities. Some suggest 

that rewarding people for appropriate knowledge-related behaviors and embedding 

knowledge-related attitudes and behaviors in performance appraisal processes represent 

a potentially significant way to use HRM practices to underpin organizational 

knowledge management efforts (e.g., Cabrera & Cabrera 2005; Oltra 2005). Moreover, 

it is also agreed that such reward systems should reflect the particular knowledge 

management strategy adopted by an organization and the type of knowledge processes 

associated with it. Hansen et al. (1999a) argue that, if a strategy pursued is codification, 

the pay and reward system should acknowledge the employee effort to codify their 

knowledge, and search for the knowledge of others. While with a personalization 

strategy, pay and reward system should recognize the effort of workers to share their 

tacit knowledge with each other (ibid). 

However, some scholars, who suggest that there may be negative consequences to 

directly linking individual, financial rewards to knowledge behaviors, challenge this 

perspective. For instance, Osterloh and Frey’s (2000) study distinguished between 

extrinsic forms of motivation (such as monetary), and intrinsic forms of motivation 

(motivation related to the benefits derived from carrying out an activity itself). They 



	 50	

concluded that financial rewards are likely to inhibit the sharing of tacit knowledge. 

Fahey, Vasconcelos and Ellis (2007) and Milne (2007) both reach a similar conclusion. 

They argue that directly associating individual rewards to knowledge sharing may mean 

people develop instrumental attitudes to such processes.  Thus, people would only 

participate in knowledge processes when they derive some form of financial reward 

from doing so, which may inhibit knowledge sharing when such rewards are not 

available (ibid). 

Another area of debate concerns whether individual or a group-based reward provides 

the best way to facilitate positive knowledge-related attitudes and behaviors. Thus, 

some research suggests that individually focused financial rewards can play a positive 

role. For example, Herowitz et al. (2003: 32) conducted a survey of Singaporean 

knowledge workers. Their findings ranked a ‘highly competitive pay package’ as the 

second most effective way to help retain knowledge workers. Furthermore, Kankanhalli 

et al. (2005) and Huang et al. (2008) also found that individually focused reward 

systems support participation in knowledge management activities. 

Others suggest that such individually focused rewards can inhibit knowledge sharing. 

They argue that such rewards create an instrumental attitude to knowledge sharing 

(Nayir & Uzuncarsili 2008). Moreover, that such reward mechanism may undermine 

people’s sense of team or community spirit (ibid). For instance, in the organization 

studies by Lam (1997), the use of individually focused rewards contributed importantly 

to the individualistic culture, which existed. This finding meant that people were 

unwilling to codify and share knowledge with colleagues. Thus, some suggest that the 

best way to develop group focused knowledge sharing is through making knowledge 

related rewards group, rather than individually focused (Cabrera & Cabrera 2005; Chen 

et al. 2011a). 

Finally, some scholars suggest that non-financial rewards such as recognition can play a 

significant role in facilitating and encouraging appropriate knowledge behaviors in 

people (e.g., Nayir & Uzuncarsili 2008; O’Dell & Hubert 2011; Teo et al. 2011). While 

Huang et al. (2008) found that financial rewards did encourage knowledge shar